Sajjad Gharaghani

2.3k total citations · 1 hit paper
82 papers, 1.8k citations indexed

About

Sajjad Gharaghani is a scholar working on Molecular Biology, Computational Theory and Mathematics and Organic Chemistry. According to data from OpenAlex, Sajjad Gharaghani has authored 82 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Molecular Biology, 40 papers in Computational Theory and Mathematics and 16 papers in Organic Chemistry. Recurrent topics in Sajjad Gharaghani's work include Computational Drug Discovery Methods (40 papers), Machine Learning in Bioinformatics (9 papers) and Protein Structure and Dynamics (9 papers). Sajjad Gharaghani is often cited by papers focused on Computational Drug Discovery Methods (40 papers), Machine Learning in Bioinformatics (9 papers) and Protein Structure and Dynamics (9 papers). Sajjad Gharaghani collaborates with scholars based in Iran, Hungary and United States. Sajjad Gharaghani's co-authors include Razieh Sheikhpour, Mohammad Ali Zare Chahooki, Mehdi Agha Sarram, M. Fatemi, Taghi Khayamian, Ali Benvidi, Saleheh Abbasi, Hadi Amiri Rudbari, Mehdi Sahihi and Karim Abbasi and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Sajjad Gharaghani

78 papers receiving 1.8k citations

Hit Papers

A Survey on semi-supervised feature selection methods 2016 2026 2019 2022 2016 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A Survey on semi-supervised feature selection methods
    2016 375 citations Razieh Sheikhpour, Sajjad Gharaghani et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sajjad Gharaghani Iran 22 663 447 397 331 288 82 1.8k
Haichun Liu China 20 533 0.8× 422 0.9× 285 0.7× 117 0.4× 94 0.3× 93 1.6k
René Thomsen Denmark 11 1.1k 1.6× 1.1k 2.5× 565 1.4× 230 0.7× 873 3.0× 11 3.4k
Jianjun Qi China 29 1.4k 2.0× 1.4k 3.1× 396 1.0× 162 0.5× 741 2.6× 124 3.5k
György Tibor Balogh Hungary 25 468 0.7× 141 0.3× 387 1.0× 107 0.3× 109 0.4× 139 2.5k
Volker Fischer United States 29 694 1.0× 290 0.6× 221 0.6× 1.1k 3.3× 175 0.6× 88 3.5k
Marjana Novič Slovenia 29 1.0k 1.6× 918 2.1× 575 1.4× 194 0.6× 137 0.5× 145 3.0k
Dávid Bajusz Hungary 21 1.1k 1.6× 1.1k 2.4× 250 0.6× 182 0.5× 152 0.5× 55 2.5k
Jianwen Chen China 35 2.0k 2.9× 189 0.4× 240 0.6× 221 0.7× 340 1.2× 148 4.0k

Countries citing papers authored by Sajjad Gharaghani

Since Specialization
Citations

This map shows the geographic impact of Sajjad Gharaghani's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sajjad Gharaghani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sajjad Gharaghani more than expected).

Fields of papers citing papers by Sajjad Gharaghani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sajjad Gharaghani. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sajjad Gharaghani. The network helps show where Sajjad Gharaghani may publish in the future.

Co-authorship network of co-authors of Sajjad Gharaghani

This figure shows the co-authorship network connecting the top 25 collaborators of Sajjad Gharaghani. A scholar is included among the top collaborators of Sajjad Gharaghani based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sajjad Gharaghani. Sajjad Gharaghani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bostanghadiri, Narjess, et al.. (2025). Impact of nafcillin and diosmin on the attachment, invasion, and stress survival of Salmonella Typhimurium. Scientific Reports. 15(1). 6308–6308.
2.
Khoshbayan, Amin, et al.. (2024). Inhibitory effects of nafcillin and diosmin on biofilm formation by Salmonella Typhimurium. BMC Microbiology. 24(1). 522–522. 2 indexed citations
3.
Gharaghani, Sajjad, et al.. (2024). Targeting SARS-CoV-2 main protease: a comprehensive approach using advanced virtual screening, molecular dynamics, and in vitro validation. Virology Journal. 21(1). 330–330. 2 indexed citations
4.
Rezaee, Elham, et al.. (2023). A Molecular Generative Model of COVID-19 Main Protease Inhibitors Using Long Short-Term Memory-Based Recurrent Neural Network. Journal of Computational Biology. 31(1). 83–98. 1 indexed citations
5.
Razzaghi, Parvin, et al.. (2023). TripletMultiDTI: Multimodal representation learning in drug-target interaction prediction with triplet loss function. Expert Systems with Applications. 232. 120754–120754. 58 indexed citations
6.
Gharaghani, Sajjad, et al.. (2023). DEDTI versus IEDTI: efficient and predictive models of drug-target interactions. Scientific Reports. 13(1). 9238–9238. 9 indexed citations
7.
Moloudizargari, Milad, et al.. (2023). Virtual screening reveals aprepitant to be a potent inhibitor of neutral sphingomyelinase 2: implications in blockade of exosome release in cancer therapy. Journal of Cancer Research and Clinical Oncology. 149(10). 7207–7216. 2 indexed citations
8.
Eslahchi, Changiz, et al.. (2022). Exploring the role of non-coding RNAs as potential candidate biomarkers in the cross-talk between diabetes mellitus and Alzheimer’s disease. Frontiers in Aging Neuroscience. 14. 955461–955461. 14 indexed citations
9.
Eslahchi, Changiz, et al.. (2022). Identification of repurposed drugs targeting significant long non-coding RNAs in the cross-talk between diabetes mellitus and Alzheimer’s disease. Scientific Reports. 12(1). 18332–18332. 6 indexed citations
10.
Sheikhpour, Razieh, et al.. (2022). Drug-target interaction prediction using reliable negative samples and effective feature selection methods. Journal of Pharmacological and Toxicological Methods. 116. 107191–107191. 3 indexed citations
11.
Gharaghani, Sajjad, et al.. (2022). Identification of new potent agonists for toll-like receptor 8 by virtual screening methods, molecular dynamics simulation, and MM-GBSA. Journal of Biomolecular Structure and Dynamics. 41(19). 10026–10036. 3 indexed citations
12.
Sheikhpour, Razieh, et al.. (2021). BRNS + SSFSM-DTI: A hybrid method for drug-target interaction prediction based on balanced reliable negative samples and semi-supervised feature selection. Chemometrics and Intelligent Laboratory Systems. 220. 104462–104462. 7 indexed citations
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Kordestani-Moghadam, Parastou, et al.. (2021). Inhibition of GSK_3β by Iridoid Glycosides of Snowberry (Symphoricarpos albus) Effective in the Treatment of Alzheimer’s Disease Using Computational Drug Design Methods. Frontiers in Chemistry. 9. 709932–709932. 11 indexed citations
16.
Rudbari, Hadi Amiri, Mehdi Sahihi, Zahra Kazemi, et al.. (2018). Chiral halogenated Schiff base compounds: green synthesis, anticancer activity and DNA-binding study. Journal of Molecular Structure. 1161. 497–511. 33 indexed citations
17.
Abbasi, Saleheh, Ali Benvidi, Sajjad Gharaghani, & Masoud Rezaeinasab. (2018). Chemometric studies of thymol binding with bovine serum albumin: A developing strategy for the successful investigation of pharmacological activity. Bioelectrochemistry. 124. 172–184. 11 indexed citations
18.
Gharaghani, Sajjad, et al.. (2017). Toward a hierarchical virtual screening and toxicity risk analysis for identifying novel CA XII inhibitors. Biosystems. 162. 35–43. 5 indexed citations
19.
Samari, Fayezeh, Mojtaba Shamsipur, Bahram Hemmateenejad, Taghi Khayamian, & Sajjad Gharaghani. (2012). Investigation of the interaction between amodiaquine and human serum albumin by fluorescence spectroscopy and molecular modeling. European Journal of Medicinal Chemistry. 54. 255–263. 124 indexed citations
20.
Gharaghani, Sajjad, Taghi Khayamian, & Fatemeh Keshavarz. (2011). A Structure‐based QSAR and Docking Study on Imidazo[1,5‐a][1,2,4]‐triazolo[1,5‐d][1,4,]benzodiazepines as Selective GABAAα5 Inverse Agonists. Chemical Biology & Drug Design. 78(4). 612–621. 7 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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